Known video analytics systems generally consist of a set of video sensors and/or other sensors arranged to monitor an area of interest. That area can be or include, merely for instance, power stations, airports, military bases, pipelines, or other areas of installations. In generally, known video analytics systems process and analyze pixels and apply some form of detection logic to identify events of concern in the area of interest.
In terms of the detection logic used to monitor the desired area, traditional video analytics systems require users to define “tripwires” or other features on the visual, pixel-based image generated by each sensor to establish the boundary, perimeter, or area to be protected. In known systems, the tripwire or other features are manually drawn or placed directly on the pixels of the view generated by each sensor, e.g., on a touchscreen display showing the view from or recorded by a surveillance camera. The user may then be prompted to save or further specify detection rules that specify the tripwires or other features in pixel space.
This pixel-based technique for defining tripwires and other features may be undesirable in various situations, such as for defining tripwires in installations that use multiple sensors for surveillance of the same physical area. In such installations, the user must inefficiently define the same tripwire or other features multiple times. That is, the user must access the video stream generated by each individual sensor, manually enter the tripwire or other features, and then repeat that process for each of the multiple sensors. Another shortcoming of such traditional systems is that the various user-drawn tripwires or other features may not exactly coincide with each other, due to human error in placing them in each sensor's view, or due to other factors. Yet another drawback is that it is technically very difficult to develop systems that automatically transfer a pixel-defined tripwire from one camera or monitor to another camera or monitor, because the pixels of one camera or monitor do not have a common frame of reference with any other camera or monitor.
Accordingly, it may be desirable to develop systems, methods, and products that address these and other shortcomings of traditional video analytics solutions.